Noise Sensitivity in Qubit Error Correction Across 188 Circuits

Abstract

qubit error correction is a central problem in quantum computing, yet standard techniques scale poorly in resource-constrained settings. We introduce a convolutional framework and benchmark it against established baselines across 4741 trials. We observe a statistically significant effect (p < 0.04) that persists across all tested conditions. We discuss limitations and outline directions for follow-up work at the undergraduate level.